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Google BigQuery vs Snowflake
May 26, 2023 | Author: Michael Stromann
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BigQuery is a serverless, highly-scalable, and cost-effective cloud data warehouse with an in-memory BI Engine and AI Platform built in.
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Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.
Google BigQuery and Snowflake are both cloud-based data warehousing platforms that offer powerful analytics capabilities, but they have some key differences in terms of architecture and features.
Google BigQuery is a serverless data warehouse that operates on Google Cloud Platform (GCP). It is designed to handle massive datasets and allows users to perform fast and scalable queries using SQL. BigQuery utilizes a columnar storage format and a distributed computing infrastructure to enable rapid query execution. It also provides seamless integration with other Google Cloud services, such as Google Cloud Storage and Google Data Studio, making it a popular choice for organizations already using GCP.
Snowflake, on the other hand, is a cloud-native data warehouse that works across multiple cloud providers, including AWS, Azure, and GCP. It features a unique architecture called the Multi-Cluster Shared Data Architecture, which separates storage and compute resources, allowing them to scale independently. Snowflake offers a range of features including automatic scaling, data sharing, and support for semi-structured data formats like JSON and Avro. It also provides a unified SQL interface for querying data across different cloud platforms.
See also: Top 10 Big Data platforms
Google BigQuery is a serverless data warehouse that operates on Google Cloud Platform (GCP). It is designed to handle massive datasets and allows users to perform fast and scalable queries using SQL. BigQuery utilizes a columnar storage format and a distributed computing infrastructure to enable rapid query execution. It also provides seamless integration with other Google Cloud services, such as Google Cloud Storage and Google Data Studio, making it a popular choice for organizations already using GCP.
Snowflake, on the other hand, is a cloud-native data warehouse that works across multiple cloud providers, including AWS, Azure, and GCP. It features a unique architecture called the Multi-Cluster Shared Data Architecture, which separates storage and compute resources, allowing them to scale independently. Snowflake offers a range of features including automatic scaling, data sharing, and support for semi-structured data formats like JSON and Avro. It also provides a unified SQL interface for querying data across different cloud platforms.
See also: Top 10 Big Data platforms
Google BigQuery vs Snowflake in our news:
2021. Cloud security startup Lacework has raised $525M
Lacework, a cloud security startup that offers a solution built on the Snowflake platform, has raised $525 million in its Series D funding round, bringing its total funding to over $1 billion. The company reported a remarkable 300% year-over-year revenue growth for the second consecutive year. Investors and customers have shown significant interest due to the comprehensive nature of Lacework's security solution. It enables companies to securely build in the cloud and covers multiple market categories to meet diverse customer needs. This includes services such as configuration and compliance, infrastructure-as-code security, vulnerability scanning during build time and runtime, as well as runtime security for cloud-native environments like Kubernetes and containers.
